<p><strong>Abstract.</strong> As the recent disaster is so difficult to predict when and where it would hit, so it requires paradigm for disaster shifts from response to preparedness. In order to respond this change, NDMI has studied disaster scientific investigation (DSI) technologies for revealing systematically the root cause of disaster and protecting repetitive recurrence.<br> The purpose of this study is to propose a convergence approach between data acquired from different types of sensors on a van-type investigation platform and UAVs of NDMI and assess their applicability for timely natural and man-made disaster mapping and monitoring. In order to evaluate its applicability for rapid disaster mapping, we pre-tested the proposed approach for NDMI site in Ulsan, Korea. For the enhancement of the direct geo-referencing accuracy of UAV imagery captured from on-board camera of DJI and the creation of more accurate map products, camera IOPs refinement and bundle adjustment were also performed with minimal GCPs. Finally, we conducted UAV data registration with LiDAR point clould for disaster mapping applications.</p>
<p><strong>Abstract.</strong> The pothole is called a road breakage where the surface of road is locally recessed. The conventional vehicle-mounted pothole detection sensor acquires data only when the vehicle directly contacts the pothole and moreover, the acquired data is limited to show the position information of the pothole based on the low-precision GPS. We have, therefore, studied the assessment methods for the road condition using the terrestrial LiDAR data to complement and improve the current methodology. In this study we subtract the low-resolution raster data from the high-resolution raster one that are taken from the terrestrial LiDAR, which is similar to the trend analysis. We assessed the proposed method using the manholes, which we assumed as potholes. It also showed that our method can improve a variety of perspectives such as time consuming, space extension and quantitative interpretation. As a result, we could expect the proposed method will be effectively used in the field of road management.</p>
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